• Atmosphere
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• v.14 no.3
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• pp.41-54
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• 2004

In this study, a brief overview on a WMO/WWRP program - The Observing System Research and Predictability Experiment (THORPEX) and discussions on perspectives and potential benefits of Asian countries are provided. THORPEX is aimed at accelerating improvements in the accuracy of 1 to 14-day high-impact weather forecasts with research objectives of: 1) predictability and dynamical processes; 2) observing systems; 3) data assimilation and observing strategies; and 4) societal and economic applications. Direct benefits of Asian countries from THORPEX include improvement of: 1) forecast skills in global models, which exerts positive impact on mesoscale forecasts; 2) typhoon forecasts through dropwindsonde observations; and 3) forecast skills for high-impact weather systems via increased observations in neighboring countries. Various indirect benefits for scientific researches are also discussed. Extensive adaptive observation studies are recommended for all high-impact weather systems coming into the Korean peninsula, and enhancement of observations in the highly sensitive regions for the forecast error growth is required to improve forecast skills in the peninsula, possibly through international collaborations with neighboring countries.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.169-174
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• 2000

In this paper, Haar wavelet-based neural network is described for the identification and control of discrete-time nonlinear dynamical systems. Wavelets are suited to depict functions with local nonlinearities and fast variations because of their intrinsic properties of finite support and self-similarity. Due to the orthonormal properties of Haar wavelet functions, wavelet neural networks result in a greatly simplified training problem. This wavelet-based scheme performs adaptively both the identification of nonlinear functions and the control of the overall system, while the multilayer neural network is applied to the control system just after its sufficient learning of the unknown functions. Simulation shows that the wavelet network can be a good alternative to a multilayer neural network with backpropagation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.480-485
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• 2005

Perspective dynamical systems arise in machine vision problems, in which only perspective observation is available. This paper considers the state estimation problem for a rigid body moving in three dimensional spaces using the image data obtained by a CCD camera or some other means. Because the motion of the rigid body and the observed data are generally corrupted by noises, it is necessary to seek a state estimation method to reduce the influence of the noises. In this paper, by means of computer simulations for a simple example, we examine the sensitivity to the noises of the nonlinear observer developed in the recent paper ([1] R. Abdursul, H. Inaba and B. Ghosh, Nonlinear observers for perspective time-invariant linear systems, Automatica, vol. 40, Issue 3, pp. 481-490, 2004) and the effectiveness of the Extended Kalman Filter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.125-128
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• 1999

A linear time-invariant model can be described either by a parametric model or by a nonparametric model. Nonparametric models, for which a priori information is not necessary, are basically the response of the dynamic system such as impulse response model and frequency models. Parametric models, such as transfer function models, can be easily described by a small number of parameters. In this paper aiming to take benefit from both types of models, we will use linear-combination of basis fuctions in an impulse response using a few parameters. We will expand and generalize the Kautz functions as basis functions for dynamical system representations and we will consider estimation problem of transfer functions using Kautz function. And so we will present the influences of poles settings of Kautz function on the identification accuracy.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.2
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• pp.351-356
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• 2013

In this article, we discuss the notions of chain prolongation functions on locally compact spaces and get some results for the concepts. We show that chain prolongation function is a cluster map.

• Journal of the Korean Mathematical Society
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• v.38 no.3
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• pp.613-621
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• 2001

In this paper we show that if a dynamical system $\phi$ has bishadowing and cyclically bishadowing properties on the chain recurrent set CR($\phi$) then all nearby continuous perturbations of $\phi$ behave chaotically on a neighborhood of each chain component of $\phi$ wheneer it has a fixed point. This is a generalization of the results obtained by Diamond et al.([3]).

• Honam Mathematical Journal
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• v.39 no.3
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• pp.401-416
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• 2017

Fractional kinetic equations are investigated in order to describe the various phenomena governed by anomalous reaction in dynamical systems with chaotic motion. Many authors have provided solutions of various families of fractional kinetic equations involving special functions. Here, in this paper, we aim at presenting solutions of certain general families of fractional kinetic equations using Prabhakar-type operators. The idea of present paper is motivated by Tomovski et al. [21].

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.81-84
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• 2000

Cellular automata are discrete dynamical systems whose behaviour is completely specified in terms of a local relation. If cellular automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose in this paper a cellular automata technique for reducing image noise. To minimize blurring effect, an algorithm based on neighborhood median computation is Preferred. Experimental results are reported.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2709-2712
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• 2003

In this paper, dynamic constraints are considered for the analysis of manipulability of robotics systems comprised of two cooperating arms. Given bounds on the torques of joint actuators for each robot, the purpose of this study is to derive the bounds of task acceleration of object carried by the system. Under the assumption of complete constraint contact, a set of examplar polytope describing acceleration bounds of two cooperating robots are included.